I think this really down plays the value of mental model or strategies for organizing code. Take a compiler: often described as a sequence of transformations on an AST, taken to the extreme in the nanopass framework. That's a really useful mental model, and you can extract that model and apply it in other contexts. For example, many business applications are a sequence of transformations on JSON. So they're basically compilers. That can be good architecture in the right situation.
You don't have to call a sequence of transformations a compiler. You can say your AST is an algebraic data type, and your transformations are folds (or structural recursions; same thing). Now you have an abstract model that isn't tied to a particular application, and you can more easily find uses for it.
If you know a bit of maths you might wonder about duals. You will find codata---objects---are the dual of algebraic data. Ok, now we're programming to interfaces. That's also useful in the right context. What's the dual of a fold? An unfold! So now we have another way of looking at transformations, from the point of view of what they produce instead of what they consume. At this point we've basically reinvented reactive programming. And on and on it goes.
You can find most of this in the literature, just not usually presented in a compact and easy to understand form.
(Note, the above description is very quick sketch and I'm not expecting anyone to understand all the details from it alone.)
I think this really down plays the value of mental model or strategies for organizing code. Take a compiler: often described as a sequence of transformations on an AST, taken to the extreme in the nanopass framework. That's a really useful mental model, and you can extract that model and apply it in other contexts. For example, many business applications are a sequence of transformations on JSON. So they're basically compilers. That can be good architecture in the right situation.
You don't have to call a sequence of transformations a compiler. You can say your AST is an algebraic data type, and your transformations are folds (or structural recursions; same thing). Now you have an abstract model that isn't tied to a particular application, and you can more easily find uses for it.
If you know a bit of maths you might wonder about duals. You will find codata---objects---are the dual of algebraic data. Ok, now we're programming to interfaces. That's also useful in the right context. What's the dual of a fold? An unfold! So now we have another way of looking at transformations, from the point of view of what they produce instead of what they consume. At this point we've basically reinvented reactive programming. And on and on it goes.
You can find most of this in the literature, just not usually presented in a compact and easy to understand form.
(Note, the above description is very quick sketch and I'm not expecting anyone to understand all the details from it alone.)
The Gary Bernhardt talk is truly special. Lots of concepts which will lead you to other interesting places